Hoe Tung Yew

Energy efficient clustering algorithm in wireless sensor networks using fuzzy logic control

In general, environment monitoring cluster based hierarchical routing protocol is among the most common protocol being opted due to the load balancing among each other sensor. Sensors are randomly deployed in a specific area to collect useful information periodically for a few months or even a few years. Therefore, battery power limitation becomes a challenging issue. It is also impractical to maintain the network lifetime by changing the battery frequently. Low energy adaptive cluster hierarchical (LEACH) is one of the common clustering protocols that will elect the cluster head based on the probability model which will possibly lead to a reduce in network lifetime due to election of cluster head with a least desired location in the network. For wireless sensor networks, the distribution of cluster head selection directly influences the networks lifetime. This paper presents factors which will affect the network lifetime and apply fuzzy logic based cluster head selection conducted in base station. The base station considers two selection criteria from sensor nodes which are energy level and distance to the base station to select the suitable cluster head that will prolong the first node die (FND) time, data stream guaranteed for every round and also increase the throughput received by the base station before FND.

Queue Management for Network Coding in Ad Hoc Networks

Network Coding has been proven to be a method that will increase the throughput of network. Network coding will perform an XOR operation in the intermediate nodes to improve the throughput of the network. The simulation of network coding in AODV to search for the route to destination will be conducted in MATLAB. This paper introduces the development of simulation to illustrate the performance of network coding in wireless ad hoc network. The simulation will calculate the transmit packet time according to the size of the packet. Lastly, average network throughput performance between AODV network without network coding and network with network coding is shown and compared.

Analysis and performance measurement of adaptive modulation and coding

Wireless spectrum is considered a limited and valuable communications resource as it influences productivity, security and our daily lives. The usage of the wireless spectrum has been given much research focus due to its limited capacity. There is currently a large amount of white spaces and spectrum holes left unused. Therefore, researchers are motivated to invent methods to utilize the spectrum more efficiently and opportunistically. Adaptive modulation and coding (AMC) is a method which adapts its transmitting parameters according to the channel state and it is used in various modern wireless communications to maximize spectrum efficiency and minimize error rate. One of the driving strengths of AMC is the Signal-to-Noise Ratio (SNR) estimation and feedback channel for adaptation. Sudden time-varying channel degrading effects sometimes require the transmission link to react appropriately so it can minimize the Bit Error Rate (BER). Thus, the objective of this paper introduces an AMC scheme which utilizes a simple moments based SNR estimator and punctured convolutional coding for spectral and quality improvement for the wireless channel.

Particle Swarm Optimization Based Resource Allocation in Orthogonal Frequency-division Multiplexing

Current cellular wireless data communications require wide availability and satisfying quality of service to keep up with the rising number of wireless devices. It is challenging for the service provider to cater to different kinds of upcoming new services and applications as data rates vary apart in that respect. For that reason, it is of paramount importance to adaptively utilize the radio resources which are limited and valuable. The ability of Orthogonal Frequency-division Multiplexing Access (OFDMA) to split the entire bandwidth into smaller sub-carriers allows adaptive resource allocation to be performed in downlink communications. However, due to the time-varying nature of the wireless channel, not all links experience the same channel response. Therefore, this situation is akin to a strategic combination problem to find the best allocation out of the huge combinations according the current channel characteristics. This paper presents an evolutionary method, particle swarm optimization (PSO), to optimally allocate the rates and sub carriers to multiple users. The results display good convergences towards the optimal solution for a minimal transmit power allocation. At transmission intervals, the cellular base station will be able to use the best allocation relating to channel conditions of any point in time.

Adaptive network selection mechanism for telecardiology system in developing countries

Inadequate telecommunication infrastructure is one of the main reason of drawback on telecardiology implementation in developing countries. A new network selection algorithm is proposed to overcome this problem by providing adaptive heterogeneous networks. The proposed algorithm finds the most suitable wireless network according to users health condition and service requirements. This algorithm adaptively adjusts the user bandwidth requirement by deactivating the lowest priority service level. The priority deactivation will provide sufficient bandwidth to support the higher priority service level when the best network has limited capacity. Simulation results show that the proposed algorithm improves the quality of services, cost effective and adaptive to the best networks. It outperforms conventional bandwidth based handover algorithm for telecardiology application.

A vertical handover management for mobile telemedicine system using heterogeneous wireless networks

Application of existing mobile telemedicine system is restricted by the imperfection of network coverage, network capacity, and mobility. In this paper, a novel telemedicine based handover decision making (THODM) algorithm is proposed for mobile telemedicine system using heterogeneous wireless networks. The proposed algorithm select the best network based on the services requirement to ensure the connected or targeted network candidate has sufficient capacity for supporting the telemedicine services. The simulation results show that the proposed algorithm minimizes the number of unnecessary handover to WLAN in high speed environment. The throughput achieved by the proposed algorithm is up to 75% and 205% higher than Cellular and RSS based schemes, respectively. Moreover, the average data transmission cost of THODM algorithm is 24% and 69.2% lower than the Cellular and RSS schemes. The proposed algorithm minimizes the average transmission cost while maintaining the telemedicine service quality at the highest level in high speed environment.

New Vertical Handover Method to Optimize Utilization of Wireless Local Area Network in High-Speed Environment

In heterogeneous wireless networks, wireless local area network (WLAN) is highly preferred by mobile terminals (MTs) owing to its high transmission bandwidth and low access cost. However, in high-speed environment, handover from a cellular network to a WLAN cell will lead to a high number of handover failures and unnecessary handovers due to the WLAN coverage limitation and will become worse at high speed. A new vertical handover method is proposed to minimize the probability of handover failure and unnecessary handover while maximizing the usage of WLAN in high-speed environment. The simulation results show that the proposed method kept the probability of handover failure and unnecessary handover below 0.5% and 1%, respectively. Compared with previous studies, the proposed method reduced the number of handover failures and unnecessary handovers up to 80.0% and 97.7%, respectively, while the MT is highly mobile. Using the proposed prediction method, the MT can benefit high bandwidth and low network access cost from the WLAN with minimum interruption regardless of speed.

Distributed beamforming with uniform circular array formation in wireless sensor networks

Collaborative beamforming (CB) has been introduced in the context of wireless sensor networks (WSNs) to enhance the communication range and energy efficiency of the networks. CB relies on a subset of nodes in the network which acts as a virtual antenna array to collectively transmit a common signal to an intended location. Due to random deployment of the sensor nodes in the networks, proper selection of participating nodes to perform distributed CB is vital to achieve better array pattern synthesis. Different topologies of the participating nodes will produce different impact on transmission gains. In this paper, a node selection method based on uniform circular array formation is presented. The analysis is carried out with the assumption that the sensor nodes are randomly distributed with uniform distribution. Statistical evaluation on the average beampattern is carried out to demonstrate the behavior and properties of the mainlobe, and sidelobe level (SLL) for the selected scheme.